Teaching Robots Social Autonomy from In Situ Human Supervision

Traditionally the behaviour of social robots has been programmed by engineers, but robots should be able to learn from their users to increase their range of application and improve their behaviour over time. This talk will start by presenting Supervised Progressively Autonomous Robot Competencies (SPARC), a machine learning framework enabling non-technical users to control and teach a robot to interact meaningfully with people in an efficient and safe way. The core premise is that the user initially remotely operates the robot, while an algorithm associates actions to states and gradually learns. Over time, the robot is able to take over from the user while still giving the user oversight of its behaviour by ensuring that every action the robot executes has been actively or passively approved by the user. The latter half of this talk will present results of a recent study evaluating SPARC in a real human-robots interaction where a robot was taught to support children in an educational activity.